Controlling the rate of bulk data multicast to a large number of receivers is difficult, due to the heterogeneity among the end systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too slow, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach toward rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different subgroups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

In our work we consider the cost optimal optical ring design problem. Given a set of wavelength demands between nodes which are arranged in a fiber ring topology, the problem is one of designing multiple optical rings stacked on the topology to carry the nodal demands with three different ring-interworking constraints. This design is to be carried out in a manner to minimize the overall equipment cost which includes two major components: a nodal optical ring switch cost and a fixed per ring cost. The ring-interworking schemes dealt with in this work are single-node ring interworking (SRI), basic dual-node ring interworking (DRI) and DRI with protection access. We have proposed an LP column generation based heuristic and a cost lower bound for each of the three constrained design cases. In numerical studies, the heuristic was observed to produce designs within 10 - 15% of the cost lower bound in the worst cases and within 1% on average.

Controlling the rate of bulk data multicast to a large number of receivers is difficult due to the heterogeneity among the end-systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too low, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach towards rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different sub-groups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

Integrated Network Design Tools (INDT) is a suite of tools being developed at Bell Labs. This suite of tools is built on a flexible software architecture based on C++ and can provide optimal network design for a mix of private line, switched voice and switched multimedia services using a mix of circuit and ATM switches and cross connects and facilities with different bandwidth granularity. INDT also has the ability to design, in a standalone mode or in conjunction with logical designs, the core transport network using mesh and/or ring topologies and using PDH or SONET/SDH products. The transport network may be designed over existing fiber routes and capacities or the tool may be used to help decide the fiber layout. We focus on a new capability within INDT, viz., SONET ring design. We present a high level description of the various submodules in the ring network design and provide an overview of the main factors that influenced our algorithm development. We also present sample studies of our approach to intra-ring load balancing as well as our economic quantification of penalties due to dual ring interconnect (DRI) and other features of interest.

Consider m offices with each operating a duplexed unit. Suppose a centrally located warehouse is to be provisioned with k spares to be used when offices experience failures. Assume that failed units are instantaneously replaced with spare units, provided a spare is available at the warehouse and the failed units are repaired and used to replenish the spare inventory. We consider two approaches for determining a suitable value for k. In the first approach, a network emergency is declared whenever the number of failed units in the network exceeds k. A simple expression for the mean time to a network emergency (MTNE) is obtained using a birth and death process model. The value of k is selected to make MTNE satisfactorily large. In this approach, it is conservatively assumed every network emergency will be service affecting. However, only when the number of failures exceeds k AND at least one office has two failures is the incident service affecting. Our second approach accounts for this distinction by evaluating the mean time to a service affecting incident (MTSI). The two approaches are compared by contrasting the different valves of k each requires to achieve a specified objective for MTNE and MTSI, respectively.

Two important quality-of-service (QoS) measures for current cellular networks are the fractions of new and handoff "calls" that are blocked due to unavailability of "channels" (radio and/or computing resources). Based on these QoS measures, we derive optimal admission control policies for three problems: minimizing a linear objective function of the new and handoff call blocking probabilities (MINOBJ), minimizing the new call blocking probability with a hard constraint on the handoff call blocking probability (MINBLOCK) and minimizing the number of channels with hard constraints on both of the blocking probabilities (MINC). We show that the well-known guard channel policy is optimal for the MLNOBJ problem, while a new fractional guard channel policy is optimal for the MINBLOCK and MINC problems. The guard channel policy reserves a set of channels for handoff calls while the fractional guard channel policy effectively reserves a non-integral number of guard channels for handoff calls by rejecting new calls with a probability that depends on the current channel occupancy. It is also shown that the fractional policy results in significant savings (20-50%) in the new call blocking probability for the MINBLOCK problem and provides some, though small, gains over the integral guard channel policy for the MINC problem. Further, we also develop computationally inexpensive algorithms for the determination of the parameters for the optimal policies.

Future high-speed networks are expected to support a wide variety of services such as voice and video, and to provide a guaranteed quality-of-service (QOS). The authors examine the issues of computing and guaranteeing QOS. Traditionally, the computation of user-oriented performance criteria such as the average delay has been carried out via steady-state analysis of queuing theoretic models of communication networks. It is shown that the steady-state computations are often not sufficient for QOS purposes in future high-speed networks. The authors provide mechanisms for computing and guaranteeing QOS criteria and consider the issue of approximate QOS criteria. It is argued that, for certain envisaged applications, traditional QOS criteria are not appropriate. A QOS criterion for such applications is proposed.>

Three different approximation techniques are examined. The performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e., the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process, and performance calculations are based only on the first two moments of the renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP attempts to capture aspects of the arrival process in a more intuitive manner than previously proposed approaches for determining the MMPP parameters and is shown to compute loss more accurately. Finally, a fluid flow approximation for computing packet loss is evaluated. For all three approaches, a unifying example, the case of multiplexing voice sources over a T1-rate link is considered. The main conclusion is that both the MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest.>

The three performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e. the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP captures aspects of the long-term correlation in the arrival process in a more intuitive manner and computes loss more accurately than previous approaches for computing the MMPP parameters. A fluid flow approximation for the superposition is evaluated on the basis of the technique of D. Anick et al. (1982). For all three approaches, the case of multiplexing voice sources over a T1-rate link is considered. Both the new MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest. The modeling of buffer overflow for general arrival processes is addressed, and modeling approaches for analyzing finite-buffer multiplexers with general arrival and service processes in a network environment are outlined.>